Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds
Abstract Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane...
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Veröffentlicht in: | Journal of bridge engineering 2022-06, Vol.27 (6) |
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creator | Wang, Guolong Wang, Kelvin C. P Yang, Guangwei Liu, Yang Li, Joshua Qiang Peters, Walt |
description | Abstract
Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane coverage. A total of 58 bridge decks in Oklahoma were evaluated via Pave3D 8K system and 3D Safety Sensor. The Pave3D 8K system collected both 0.5-mm 3D height images, 2D grayscale images, and longitudinal profiler at highway speeds for bridge deck assessment in terms of distress detection and roughness evaluation. A Deep Learning-based method was applied to detect cracks automatically, and a manual tool was developed to label other distress for bridge decks and joints from the obtained images. Further, the 0.5-mm 3D images and longitudinal profiler data were combined to identify locations with roughness issues and the causes on bridge decks or approach slabs. Finally, the 3D Safety Sensor acquired 0.1-mm 2D/3D images for hydroplaning speed prediction of bridge decks. The evaluation results demonstrate the efficacy of the sub-mm 3D laser imaging technology for nondestructive bridge deck conditions and safety evaluations. |
doi_str_mv | 10.1061/(ASCE)BE.1943-5592.0001888 |
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Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane coverage. A total of 58 bridge decks in Oklahoma were evaluated via Pave3D 8K system and 3D Safety Sensor. The Pave3D 8K system collected both 0.5-mm 3D height images, 2D grayscale images, and longitudinal profiler at highway speeds for bridge deck assessment in terms of distress detection and roughness evaluation. A Deep Learning-based method was applied to detect cracks automatically, and a manual tool was developed to label other distress for bridge decks and joints from the obtained images. Further, the 0.5-mm 3D images and longitudinal profiler data were combined to identify locations with roughness issues and the causes on bridge decks or approach slabs. Finally, the 3D Safety Sensor acquired 0.1-mm 2D/3D images for hydroplaning speed prediction of bridge decks. The evaluation results demonstrate the efficacy of the sub-mm 3D laser imaging technology for nondestructive bridge deck conditions and safety evaluations.</description><identifier>ISSN: 1084-0702</identifier><identifier>EISSN: 1943-5592</identifier><identifier>DOI: 10.1061/(ASCE)BE.1943-5592.0001888</identifier><language>eng</language><publisher>New York: American Society of Civil Engineers</publisher><subject>Bridge construction ; Bridge decks ; Bridge inspection ; Bridge maintenance ; Bridges ; Civil engineering ; Deep learning ; Evaluation ; Flaw detection ; Hand tools ; Hydroplaning ; Image acquisition ; Imaging techniques ; Inspection ; Joints (timber) ; Lasers ; Nondestructive testing ; Roughness ; Safety ; Sensors ; Slabs ; Technical Papers ; Technology ; Three dimensional imaging</subject><ispartof>Journal of bridge engineering, 2022-06, Vol.27 (6)</ispartof><rights>2022 American Society of Civil Engineers</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a337t-4dbfa8b53aadfed343d9dd9340a7c50ad67247b0ceef1da8c1189d3123f79e473</citedby><cites>FETCH-LOGICAL-a337t-4dbfa8b53aadfed343d9dd9340a7c50ad67247b0ceef1da8c1189d3123f79e473</cites><orcidid>0000-0002-0870-2440</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://ascelibrary.org/doi/pdf/10.1061/(ASCE)BE.1943-5592.0001888$$EPDF$$P50$$Gasce$$H</linktopdf><linktohtml>$$Uhttp://ascelibrary.org/doi/abs/10.1061/(ASCE)BE.1943-5592.0001888$$EHTML$$P50$$Gasce$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,76193,76201</link.rule.ids></links><search><creatorcontrib>Wang, Guolong</creatorcontrib><creatorcontrib>Wang, Kelvin C. P</creatorcontrib><creatorcontrib>Yang, Guangwei</creatorcontrib><creatorcontrib>Liu, Yang</creatorcontrib><creatorcontrib>Li, Joshua Qiang</creatorcontrib><creatorcontrib>Peters, Walt</creatorcontrib><title>Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds</title><title>Journal of bridge engineering</title><description>Abstract
Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane coverage. A total of 58 bridge decks in Oklahoma were evaluated via Pave3D 8K system and 3D Safety Sensor. The Pave3D 8K system collected both 0.5-mm 3D height images, 2D grayscale images, and longitudinal profiler at highway speeds for bridge deck assessment in terms of distress detection and roughness evaluation. A Deep Learning-based method was applied to detect cracks automatically, and a manual tool was developed to label other distress for bridge decks and joints from the obtained images. Further, the 0.5-mm 3D images and longitudinal profiler data were combined to identify locations with roughness issues and the causes on bridge decks or approach slabs. Finally, the 3D Safety Sensor acquired 0.1-mm 2D/3D images for hydroplaning speed prediction of bridge decks. The evaluation results demonstrate the efficacy of the sub-mm 3D laser imaging technology for nondestructive bridge deck conditions and safety evaluations.</description><subject>Bridge construction</subject><subject>Bridge decks</subject><subject>Bridge inspection</subject><subject>Bridge maintenance</subject><subject>Bridges</subject><subject>Civil engineering</subject><subject>Deep learning</subject><subject>Evaluation</subject><subject>Flaw detection</subject><subject>Hand tools</subject><subject>Hydroplaning</subject><subject>Image acquisition</subject><subject>Imaging techniques</subject><subject>Inspection</subject><subject>Joints (timber)</subject><subject>Lasers</subject><subject>Nondestructive testing</subject><subject>Roughness</subject><subject>Safety</subject><subject>Sensors</subject><subject>Slabs</subject><subject>Technical Papers</subject><subject>Technology</subject><subject>Three dimensional imaging</subject><issn>1084-0702</issn><issn>1943-5592</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kM1OwzAQhC0EEqXwDhZc4JBix05sc-tPoJUqOLQ9Gyd20pQmKXZS1LcnUQucOO1qNDOr_QC4xWiAUYgf74eLcfQwigZYUOIFgfAHCCHMOT8DvV_tvN0Rpx5iyL8EV85tWg8NBemB99eq1MbVtknqfG_gyOY6M3Bikg8Y7dW2UXVelXDl8jKDiyb2igKSCZwrZyycFSrr9KVJ1mW1rbIDVDWc5tn6Sx3gYmeMdtfgIlVbZ25Osw9Wz9FyPPXmby-z8XDuKUJY7VEdp4rHAVFKp0YTSrTQWhCKFEsCpHTIfMpilBiTYq14gjEXmmCfpEwYykgf3B17d7b6bNqP5KZqbNmelH5Ihc8xC4LW9XR0JbZyzppU7mxeKHuQGMmOqJQdUTmKZEdPdvTkiWgbDo9h5RLzV_-T_D_4DUmSer0</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Wang, Guolong</creator><creator>Wang, Kelvin C. P</creator><creator>Yang, Guangwei</creator><creator>Liu, Yang</creator><creator>Li, Joshua Qiang</creator><creator>Peters, Walt</creator><general>American Society of Civil Engineers</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TN</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-0870-2440</orcidid></search><sort><creationdate>20220601</creationdate><title>Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds</title><author>Wang, Guolong ; Wang, Kelvin C. P ; Yang, Guangwei ; Liu, Yang ; Li, Joshua Qiang ; Peters, Walt</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a337t-4dbfa8b53aadfed343d9dd9340a7c50ad67247b0ceef1da8c1189d3123f79e473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bridge construction</topic><topic>Bridge decks</topic><topic>Bridge inspection</topic><topic>Bridge maintenance</topic><topic>Bridges</topic><topic>Civil engineering</topic><topic>Deep learning</topic><topic>Evaluation</topic><topic>Flaw detection</topic><topic>Hand tools</topic><topic>Hydroplaning</topic><topic>Image acquisition</topic><topic>Imaging techniques</topic><topic>Inspection</topic><topic>Joints (timber)</topic><topic>Lasers</topic><topic>Nondestructive testing</topic><topic>Roughness</topic><topic>Safety</topic><topic>Sensors</topic><topic>Slabs</topic><topic>Technical Papers</topic><topic>Technology</topic><topic>Three dimensional imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Guolong</creatorcontrib><creatorcontrib>Wang, Kelvin C. P</creatorcontrib><creatorcontrib>Yang, Guangwei</creatorcontrib><creatorcontrib>Liu, Yang</creatorcontrib><creatorcontrib>Li, Joshua Qiang</creatorcontrib><creatorcontrib>Peters, Walt</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of bridge engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Guolong</au><au>Wang, Kelvin C. P</au><au>Yang, Guangwei</au><au>Liu, Yang</au><au>Li, Joshua Qiang</au><au>Peters, Walt</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds</atitle><jtitle>Journal of bridge engineering</jtitle><date>2022-06-01</date><risdate>2022</risdate><volume>27</volume><issue>6</issue><issn>1084-0702</issn><eissn>1943-5592</eissn><abstract>Abstract
Periodic bridge deck inspection is critically important in bridge management and maintenance. This paper presents a comprehensive bridge deck evaluation using sub-mm three-dimensional (3D) laser imaging technology in a nondestructive and efficient manner at highway speeds with complete lane coverage. A total of 58 bridge decks in Oklahoma were evaluated via Pave3D 8K system and 3D Safety Sensor. The Pave3D 8K system collected both 0.5-mm 3D height images, 2D grayscale images, and longitudinal profiler at highway speeds for bridge deck assessment in terms of distress detection and roughness evaluation. A Deep Learning-based method was applied to detect cracks automatically, and a manual tool was developed to label other distress for bridge decks and joints from the obtained images. Further, the 0.5-mm 3D images and longitudinal profiler data were combined to identify locations with roughness issues and the causes on bridge decks or approach slabs. Finally, the 3D Safety Sensor acquired 0.1-mm 2D/3D images for hydroplaning speed prediction of bridge decks. The evaluation results demonstrate the efficacy of the sub-mm 3D laser imaging technology for nondestructive bridge deck conditions and safety evaluations.</abstract><cop>New York</cop><pub>American Society of Civil Engineers</pub><doi>10.1061/(ASCE)BE.1943-5592.0001888</doi><orcidid>https://orcid.org/0000-0002-0870-2440</orcidid></addata></record> |
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subjects | Bridge construction Bridge decks Bridge inspection Bridge maintenance Bridges Civil engineering Deep learning Evaluation Flaw detection Hand tools Hydroplaning Image acquisition Imaging techniques Inspection Joints (timber) Lasers Nondestructive testing Roughness Safety Sensors Slabs Technical Papers Technology Three dimensional imaging |
title | Nondestructive Bridge Deck Evaluation Using Sub-mm 3D Laser Imaging Technology at Highway Speeds |
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